{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T13:44:46Z","timestamp":1777556686287,"version":"3.51.4"},"reference-count":35,"publisher":"SAGE Publications","issue":"2","license":[{"start":{"date-parts":[[2021,11,24]],"date-time":"2021-11-24T00:00:00Z","timestamp":1637712000000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"},{"start":{"date-parts":[[2021,11,24]],"date-time":"2021-11-24T00:00:00Z","timestamp":1637712000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"DOI":"10.13039\/100010663","name":"H2020 European Research Council","doi-asserted-by":"publisher","award":["679681"],"award-info":[{"award-number":["679681"]}],"id":[{"id":"10.13039\/100010663","id-type":"DOI","asserted-by":"publisher"}]},{"name":"National Research, Development and Innovation Fund of Hungary","award":["2019-1.3.1-KK-2019-00007"],"award-info":[{"award-number":["2019-1.3.1-KK-2019-00007"]}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["J Diabetes Sci Technol"],"published-print":{"date-parts":[[2023,3]]},"abstract":"<jats:sec>\n                    <jats:title>Objective:<\/jats:title>\n                    <jats:p>Characterizing blood glucose curves and providing precise patient level risk assessment of hyperglycemia using extreme value statistics and comparing these assessments with traditional indicators of glycemic variability which are not designed to specifically capture the risk of hyperglycemia.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Research Design and Methods:<\/jats:title>\n                    <jats:p>One year return level (blood glucose level exceeded exactly once every year on average) and probability of exceeding and expected time spent above certain thresholds (600 and 400 mg\/dL) per year were calculated. As a comparison, traditional metrics for glycemic variability were determined too. The effect of body mass index on extremes was also investigated using non-stationary models. Metrics were calculated on a dataset containing 170.8 patient-years of measurements of 226 patients.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results:<\/jats:title>\n                    <jats:p>Nine high-risk patients were identified with the novel metrics: their estimated time spent above 600 mg\/dL per year were above 2 hours. These patients were at moderate risk according to the traditional metrics. Higher body mass index was associated with more extreme glucose levels.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions:<\/jats:title>\n                    <jats:p>Through these estimates it is possible to assess each patient\u2019s individual clinical risk of hyperglycemia even beyond the observed blood glucose levels and detection limits. Additionally, it allows the assessment of the impact of clinical characteristics and treatments on blood glucose control in a novel, mathematically well-founded and potentially clinically more useful way than the already existing indicators.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/19322968211059547","type":"journal-article","created":{"date-parts":[[2021,11,24]],"date-time":"2021-11-24T04:15:13Z","timestamp":1637727313000},"page":"400-408","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":3,"title":["The Use of Extreme Value Statistics to Characterize Blood Glucose Curves and Patient Level Risk Assessment of Patients With Type I Diabetes"],"prefix":"10.1177","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7250-7888","authenticated-orcid":false,"given":"M\u00e1ty\u00e1s","family":"Szigeti","sequence":"first","affiliation":[{"name":"Imperial Clinical Trials Unit, Imperial College London, London, UK"},{"name":"Physiological Controls Research Center, Budapest, Hungary"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tam\u00e1s","family":"Ferenci","sequence":"additional","affiliation":[{"name":"Physiological Controls Research Center, Budapest, Hungary"},{"name":"Department of Statistics, Corvinus University of Budapest, Budapest, Hungary"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3188-0800","authenticated-orcid":false,"given":"Levente","family":"Kov\u00e1cs","sequence":"additional","affiliation":[{"name":"Physiological Controls Research Center, Budapest, Hungary"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2021,11,24]]},"reference":[{"key":"e_1_3_3_2_2","doi-asserted-by":"publisher","DOI":"10.1049\/ip-smt:20000841"},{"key":"e_1_3_3_3_2","volume-title":"Paper presented at the Society of Naval Architects and Marine Engineers (SNAME);","author":"Ochi MK.","unstructured":"Ochi MK. Principles of extreme value statistics and their application. Paper presented at the Society of Naval Architects and Marine Engineers (SNAME); October 1981; Arlington, VA."},{"key":"e_1_3_3_4_2","doi-asserted-by":"publisher","DOI":"10.1029\/2009WR008876"},{"key":"e_1_3_3_5_2","first-page":"1","article-title":"Modelling record times in sport with extreme value methods","volume":"10","author":"Adam M","year":"2016","unstructured":"Adam M, Tawn JA. Modelling record times in sport with extreme value methods. 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